alps k6989v1_64_pre
Geekbench ML Score
1067
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 09:37 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | alps k6989v1_64_pre |
| Model ID | alps k6989v1_64_pre |
| Motherboard | k6989v1_64_pre |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 10.97 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
650
121.7 IPS |
|
|
Image Classification (F16)
|
100% |
673
125.9 IPS |
|
|
Image Classification (I8)
|
97% |
850
159.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
860
14.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
854
14.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
982
16.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1087
1.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
986
1.19 IPS |
|
|
Pose Estimation (I8)
|
100% |
4528
5.48 IPS |
|
|
Object Detection (F32)
|
100% |
572
42.7 IPS |
|
|
Object Detection (F16)
|
100% |
578
43.2 IPS |
|
|
Object Detection (I8)
|
61% |
822
61.4 IPS |
|
|
Face Detection (F32)
|
100% |
1445
17.2 IPS |
|
|
Face Detection (F16)
|
100% |
1447
17.2 IPS |
|
|
Face Detection (I8)
|
86% |
2069
24.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1154
8.95 IPS |
|
|
Depth Estimation (F16)
|
100% |
1102
8.55 IPS |
|
|
Depth Estimation (I8)
|
95% |
1849
14.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1715
2.26 IPS |
|
|
Style Transfer (F16)
|
100% |
1582
2.08 IPS |
|
|
Style Transfer (I8)
|
98% |
4185
5.50 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
772
27.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
761
27.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2172
77.6 IPS |
|
|
Text Classification (F32)
|
100% |
680
977.4 IPS |
|
|
Text Classification (F16)
|
100% |
689
989.8 IPS |
|
|
Text Classification (I8)
|
92% |
487
699.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1287
23.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1170
21.5 IPS |
|
|
Machine Translation (I8)
|
64% |
400
7.36 IPS |
